Quantitative Methods for Food Systems Research

Chris Donovan

Food Systems Data Scientist
Food Systems Research Institute

November 5, 2025

Quantitative Methods

  • What are they good for
  • What are they not good for
  • Standard toolkit
    • Regression and friends
  • building on that
    • directed acyclic graphs
    • structural equation model
  • system modeling:
    • fuzzy cognitive mapping
    • agent-based
    • system dynamics
  • bayesian methods

A picture of a field at Intervale Farm.

Intervale Farm, Sally McCay, UVM Photo

(Mis-)Interpreting Quantitative Results

A picture of a field at Intervale Farm.

Intervale Farm, Sally McCay, UVM Photo
  • Berksen’s paradox
  • Image of a DAG, chain collider

A picture of a field at Intervale Farm.

Intervale Farm, Sally McCay, UVM Photo

  • People misunderstand graphs
{r}
plot(iris)

Approaching a Quantitative Analysis

  • Power, sample size, outliers, analyses
  • Think many analyses
  • consider preregistration
  • DAGs asnd Berksen
  • do it
  • distributional assumptions
  • missing data, unknown trends
  • Reproducibility
  • Version Control
  • Do it

References

Anderson, Samantha F. 2020. “Misinterpreting p: The Discrepancy Between p Values and the Probability the Null Hypothesis Is True, the Influence of Multiple Testing, and Implications for the Replication Crisis.” Psychological Methods 25 (5): 596–609. https://doi.org/10.1037/met0000248.
Cumming, Geoff, and Sue Finch. 2005. “Inference by Eye: Confidence Intervals and How to Read Pictures of Data.” American Psychologist 60 (2): 170–80. https://doi.org/10.1037/0003-066X.60.2.170.
Zhang, Sam, Patrick R. Heck, Michelle N. Meyer, Christopher F. Chabris, Daniel G. Goldstein, and Jake M. Hofman. 2023. “An Illusion of Predictability in Scientific Results: Even Experts Confuse Inferential Uncertainty and Outcome Variability.” Proceedings of the National Academy of Sciences 120 (33): e2302491120. https://doi.org/10.1073/pnas.2302491120.